# Granite 4.2 30B vs Ling-3.1-flash-1019 (slim)

> Granite 4.2 30B scores 61 (C) to Ling-3.1-flash-1019's 54.8 (C) for open-weight models you run yourself. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ling-3-1-flash-1019.md (~10,350 tokens) · this version ~780 tokens · JSON https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ling-3-1-flash-1019.json · canonical https://www.anchorterminal.com/compare/granite-4-2-30b-vs-ling-3-1-flash-1019
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-10
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Granite 4.2 30B scores 61 (C) on agent readiness against Ling-3.1-flash-1019's 54.8 (C), and leads in every scored category. Both do open-weight models you run yourself.

- Granite 4.2 30B: C 61, rank #65 of 160 open-weight models · https://www.anchorterminal.com/tools/granite-4-2-30b.min.md
- Ling-3.1-flash-1019: C 54.8, rank #126 of 160 open-weight models · https://www.anchorterminal.com/tools/ling-3-1-flash-1019.min.md
- Granite 4.2 30B, good for Agents that want a documented, signed, Apache 2.0 reasoning model with tool calling on a 24 GB card Ahead on Reach, 90 against 60; Risk, 55 against 45; Agent interface, 85 against 60; Documentation and upkeep, 87 against 56.
- Ling-3.1-flash-1019, good for Teams with a multi-GPU server that want an MIT-licensed flagship for long agent runs and coding

| Category | Granite 4.2 30B | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Capability (35%) | pending | pending |
| Reach (25%) | 90 | 60 |
| Risk (20%) | 55 | 45 |
| Agent interface (10%) | 85 | 60 |
| Documentation and upkeep (10%) | 87 | 56 |

| Fact (where they differ) | Granite 4.2 30B | Ling-3.1-flash-1019 |
| --- | --- | --- |
| Vendor | IBM | inclusionAI (Ant Group) |
| Licence | Apache-2.0 | MIT |
| Last release | 2026-09-04 | 2026-11-04 |

Why the edge:
- Documentation and upkeep, Granite 4.2 30B +31: Granite 4.2 30B 87 (Model card 17, Intended use (best for), limitations (ethical considerations and limitations), architecture, parameters (30B), context length (128K native) and 1…); Ling-3.1-flash-1019 56 (Model card 11, Intended use (complex reasoning, multi-step tasks and agentic workflows), architecture, parameters (560B total, 25B active) and context (1M claim…)
- Reach, Granite 4.2 30B +30: Granite 4.2 30B 90 (Memory 25, IBM's own 4-bit MLX build granite-4.2-30b-q4-mlx is 16.47 GB, and 16.47 GB × 1.2 = 19.8 GB, which fits 24 GB but not 16 GB.); Ling-3.1-flash-1019 60 (Memory 0, inclusionAI's only build is the FP8 release at 573.78 GB, × 1.2 = 688.5 GB, above 256 GB, and no runtime's library has a build.)
- Agent interface, Granite 4.2 30B +25: Granite 4.2 30B 85 (Chat template 20, chat_template.jinja in the repository, with roles, tools, tool responses, the thinking switch and low effort.); Ling-3.1-flash-1019 60 (Chat template 20, chat_template.jinja in the repository (6,042 characters), which handles tools, the thinking switch and preserved reasoning.)
- Risk, Granite 4.2 30B +10: Granite 4.2 30B 55 (File safety 15, safetensors only, no .bin, .pt or .pth files (25).); Ling-3.1-flash-1019 45 (File safety 15, safetensors only, no .bin, .pt or .pth files (25), less 10 because the card's documented vLLM command passes --trust-remote-code, which runs the…)